We have taken advantage of the metabolic alteration of methionine (Met) dependence which frequently occurs in many if not all types of human cancer but not normal tissue which is the inability to grow when homocysteine (Hcy) is substituted for Met in the growth medium in vitro. In Met-free, Hcy-containing medium cancer cells reversibly arrest in the late-S/G2 phase of the cell cycle. The specific arrest allows selective synchronization and attack against the cancer cells by cell-cycle-specific drugs and drugs which interact with Met transport and metabolism such as methotrexate and cisplatin. In order for Met-dependent chemotherapy to be highly effective in vivo there must be a means to greatly reduce the circulating levels of Met. Therefore, we propose here to continue the purification, genetic engineering and protein engineering of methioninase (Metase) from a Pseudomonas such that it can be effective as an anticancer drug for humans. The purified enzyme's efficacy in Met-dependent chemotherapy will be carried out by sequencing the protein and using the sequence information to design and synthesize mixed oligonucleotide probes that will either be used to prime the polymerase chain reaction and synthesize mixed oligonucleotide probes that will either be used to prime the polymerase chain reaction (PCR) to directly clone the methioninase coding region, or as probes to identify DNA clones containing the Metase gene from genomic libraries. The cloned gene will then be sequenced and amber codon mutations will be inserted in various parts of the gene by site-specific mutagenesis. Utilizing synthetic suppressor tRNA genes, the various amber mutations of the gene will be suppressed in E. coli with suppressors that insert, in series, up to 12 different amino acids to attempt to identify a Metase optimized for clinical use, utilizing the parameters of Km, Vmax, and long pharmacological half life. We will use site-directed missense mutagenesis to generate the clone to produce the Metase in E. coli based on the amber suppression data.